Cameras have been used in a wide range of industrial applications and are being used in an increasingly larger number of applications. For example, cameras are used in place of human eyes in many automatic industrial applications, including monitoring of robots on an assembly line, product quality testing, medical diagnosis, security, and recognition of an image captured by an imaging system.
In general, when a high resolution image needs to be obtained, a narrow-angle lens is placed in front of a camera, and when a wider area needs to be photographed, a wide-angle lens is placed in front of the camera. A wide-angle lens allows a wide angle of view, but has a disadvantage in that resolution decreases from the center to outer portions of the lens.
The wide-angle lens also has a disadvantage in that radial distortion increases from the center to the outer portions of the lens. Such radial distortion is a main cause of resolution degradation.
FIGS. 1A and 1B illustrate a pattern image and a web image in which radial distortion is caused by a wide-angle lens, respectively. As described above, resolution decreases and radial distortion increases from the center to outer portions of the lens.
A known method of correcting lens distortion is divided into a metric method and a non-metric method. The metric method corrects a distortion in an image using the intrinsic and extrinsic parameters of a camera model that may affect the lens distortion. The intrinsic and extrinsic parameters are measured on the basis of reference points. The non-metric method does not rely on reference points but relies on the fact that straight lines in a scene must always project to straight lines in an image. The non-metric method corrects distortion by fitting curved lines caused by lens distortion into straight lines.
In the metric method, using more reference points may increase the accuracy of distortion coefficients. Thus, the metric method may require a plurality of pattern images in extracting the reference points. In addition, the metric method may introduce severe measurement errors that occur when the intrinsic and extrinsic parameters are obtained.
In the non-metric method, the distortion coefficients can be obtained by using a single image without the use of any reference points. However, in the non-metric method, the distortion coefficients can be measured only when the image contains an object having linear components. In addition, automatic distortion correcting algorithms are very sensitive to noise in the non-metric method.